Summary of chi-square:
Here's a summary of the steps needed to do a chi-square goodness of fit test:
In the Dilbert example...
|1. Decide on a null hypothesis -- a "model" that the data should fit||Dilbert's null hypothesis was that the sickdays were randomly distributed.|
|2. Note your "expected" and "observed" values||Since 40% of weekdays fall on Monday or Friday, the same should be true of sickdays -- or 40 out of 100. The observed value was 42 out of 100.|
|3. Calculate the chi-square [add up (o-e)2 / e ]||We got 0.166|
|4. Look up the chi-square-crit based on your p-value and degrees of freedom.||With p=0.05 and df=1, chi-square-crit = 3.84.|
|5. Determine whether chi-square-calc < chi-square crit-- if so, we say the model fits the data well.||Chi-square-crit > chi-square-calc, so the deviations are small and the data fit the null model of random sickdays.|
Copyright University of Maryland, 2007
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